Open source software is increasingly driven by a combination of independent and professional developers, the former volunteers and the later hired by a software company to contribute to the project to support commercial product development. This mix of developers has been referred to as OSS 2.0. However, we do not fully understand the coordination spanning individuals, teams, and organizations in OSS 2.0. Using Actor-Network Theory (ANT), we describe how coordination and power dynamics unfold and how technological artifacts both display actions and mediate coordination efforts. Internal coordination within an organization was reported to create competing networks against the network for the whole OSS community by breaking the alignments of interests. ANT shows how software development tools and code, as active actors, exercise agency in attracting developers to work on problems and informing the layers of collaboration. We discuss the theoretical and practical implications of the changing nature of OSS.

Open source software projects are increasingly driven by a combination of independent and professional developers, the former volunteers and the later hired by a company to contribute to the project to support commercial product development. This mix of developers has been referred to as OSS 2.0. However, we do not fully understand the multi-layered coordination spanning individuals, teams, and organizations. Using Actor-Network Theory (ANT), we describe how coordination and power dynamics unfold among developers and how different tools and artifacts both display activities and mediate coordination efforts. Internal communication within an organization was reported to cause broken links in the community, duplication of work, and political tensions. ANT shows how tools and code can exercise agency and alter a software development process as an equivalently active actor of the scene. We discuss the theoretical and practical implications of the changing nature of open source software development.

This paper explores the skills needed to be a data scientist. Specifically, we report on a mixed method study of a project-based data science class, where we evaluated student effectiveness with respect to dividing a project into appropriately sized modular tasks, which we termed task modularity. Our results suggest that while data science students can appreciate the value of task modularity, they struggle to achieve effective task modularity. As a first step, based our study, we identified six task decomposition best practices. However, these best practices do not fully address this gap of how to enable data science students to effectively use task modularity. We note that while computer science/information system programs typically teach modularity (e.g., the decomposition process and abstraction), and there remains a need identify a corresponding model to that used for computer science / information system students, to teach modularity to data science students.

We present a conceptual framework for socio-technical affordances for stigmergic coordination, that is, coordination supported by a shared work product. Based on research on free/libre open source software development, we theorize that stigmergic coordination depends on three sets of socio-technical affordances: the visibility and combinability of the work, along with defined genres of work contributions. As a demonstration of the utility of the developed framework, we use it as the basis for the design and implementation of a system, MIDST, that supports these affordances and that we thus expect to support stigmergic coordination. We describe an initial assessment of the impact of the tool on the work of project teams of three to six data-science students that suggests that the tool was useful but also in need of further development. We conclude with plans for future research and an assessment of theory-driven system design.